Fitz Veronika, El Abiead Yasin, Berger Daniel, Koellensperger Gunda
Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Vienna, Austria.
Front Mol Biosci. 2022 Jul 18;9:857505. doi: 10.3389/fmolb.2022.857505. eCollection 2022.
Covering a wide spectrum of molecules is essential for global metabolome assessment. While metabolomics assays are most frequently carried out in microbore LC-MS analysis, reducing the size of the analytical platform has proven its ability to boost sensitivity for specific - applications. In this study, we elaborate the impact of LC miniaturization on exploratory small-molecule LC-MS analysis, focusing on chromatographic properties with critical impact on peak picking and statistical analysis. We have assessed a panel of small molecules comprising endogenous metabolites and environmental contaminants covering three flow regimes-analytical, micro-, and nano-flow. Miniaturization to the micro-flow regime yields moderately increased sensitivity as compared to the nano setup, where median sensitivity gains around 80-fold are observed in protein-precipitated blood plasma extract. This gain resulting in higher coverage at low µg/L concentrations is compound dependent. At the same time, the nano-LC-high-resolution mass spectrometry (HRMS) approach reduces the investigated chemical space as a consequence of the trap-and-elute nano-LC platform. Finally, while all three setups show excellent retention time stabilities, rapid gradients jeopardize the peak area repeatability of the nano-LC setup. Micro-LC offers the best compromise between improving signal intensity and metabolome coverage, despite the fact that only incremental gains can be achieved. Hence, we recommend using micro-LC for wide-target small-molecule trace bioanalysis and global metabolomics of abundant samples.
覆盖广泛的分子对于全面的代谢组评估至关重要。虽然代谢组学分析最常通过微径液相色谱 - 质谱联用（LC-MS）分析进行，但减小分析平台的尺寸已证明其能够提高特定应用的灵敏度。在本研究中，我们阐述了液相色谱小型化对探索性小分子LC-MS分析的影响，重点关注对峰识别和统计分析有关键影响的色谱特性。我们评估了一组小分子，包括内源性代谢物和环境污染物，涵盖三种流速模式——分析流速、微流速和纳流速。与纳流设置相比，小型化到微流速模式可适度提高灵敏度，在蛋白质沉淀的血浆提取物中观察到灵敏度中位数提高约80倍。这种在低μg/L浓度下实现更高覆盖率的增益因化合物而异。同时，由于捕集 - 洗脱纳流液相色谱平台，纳流液相色谱 - 高分辨率质谱（HRMS）方法减少了所研究的化学空间。最后，虽然所有三种设置都显示出出色的保留时间稳定性，但快速梯度会危及纳流液相色谱设置的峰面积重复性。微流液相色谱在提高信号强度和代谢组覆盖率之间提供了最佳折衷，尽管只能实现渐进式增益。因此，我们建议将微流液相色谱用于广泛目标的小分子痕量生物分析和丰富样品的全局代谢组学研究。
